Similarities and differences in the sensitivity of soil organic matter (SOM) dynamics to biogeochemical parameters for different vegetation inputs and climates

The biogeochemical complexity of environmental models is increasing continuously and model reliability must be reanalysed when new implementations are brought about. This work aims to identify influential biogeochemical parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse ga...

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Veröffentlicht in:Stochastic environmental research and risk assessment 2020-12, Vol.34 (12), p.2229-2244
Hauptverfasser: Ceriotti, G., Tang, F. H. M., Maggi, F.
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Tang, F. H. M.
Maggi, F.
description The biogeochemical complexity of environmental models is increasing continuously and model reliability must be reanalysed when new implementations are brought about. This work aims to identify influential biogeochemical parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse gas emissions in different ecosystems and climates predicted by a physically-based mechanistic model. This explicitly accounts for four pools of organic polymers, seven pools of organic monomers, five microbial functional groups, and inorganic N and C species. We first benchmarked our model against vertical SOM profiles measured in a temperate forest in North-Eastern Bavaria, Germany (Staudt and Foken in Documentation of reference data for the experimental areas of the Bayreuth Centre for Ecology and Environmental Research (BayCEER) at the Waldstein site. Univ, Bayreuth, Department of Micrometeorology, 2007). Next, we conducted a sensitivity analysis to biogeochemical parameters using modified Morris indices for target SOM pools and gas emissions from a tropical, a temperate, and a semi-arid grassland in Australia. We found that greenhouse gas emissions, the SOM stock, and the fungi-to-bacteria ratio in the top soil were more sensitive to the mortality of aerobic bacteria than other biogeochemical parameters. The larger CO 2 emission rates in forests than in grasslands were explained by a greater dissolved SOM content. Finally, we found that the soil N availability was largely controlled by vegetation inputs in forests and by atmospheric fixation in grasslands.
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H. M. ; Maggi, F.</creator><creatorcontrib>Ceriotti, G. ; Tang, F. H. M. ; Maggi, F.</creatorcontrib><description>The biogeochemical complexity of environmental models is increasing continuously and model reliability must be reanalysed when new implementations are brought about. This work aims to identify influential biogeochemical parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse gas emissions in different ecosystems and climates predicted by a physically-based mechanistic model. This explicitly accounts for four pools of organic polymers, seven pools of organic monomers, five microbial functional groups, and inorganic N and C species. We first benchmarked our model against vertical SOM profiles measured in a temperate forest in North-Eastern Bavaria, Germany (Staudt and Foken in Documentation of reference data for the experimental areas of the Bayreuth Centre for Ecology and Environmental Research (BayCEER) at the Waldstein site. Univ, Bayreuth, Department of Micrometeorology, 2007). Next, we conducted a sensitivity analysis to biogeochemical parameters using modified Morris indices for target SOM pools and gas emissions from a tropical, a temperate, and a semi-arid grassland in Australia. We found that greenhouse gas emissions, the SOM stock, and the fungi-to-bacteria ratio in the top soil were more sensitive to the mortality of aerobic bacteria than other biogeochemical parameters. The larger CO 2 emission rates in forests than in grasslands were explained by a greater dissolved SOM content. 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H. M.</creatorcontrib><creatorcontrib>Maggi, F.</creatorcontrib><title>Similarities and differences in the sensitivity of soil organic matter (SOM) dynamics to biogeochemical parameters for different vegetation inputs and climates</title><title>Stochastic environmental research and risk assessment</title><addtitle>Stoch Environ Res Risk Assess</addtitle><description>The biogeochemical complexity of environmental models is increasing continuously and model reliability must be reanalysed when new implementations are brought about. This work aims to identify influential biogeochemical parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse gas emissions in different ecosystems and climates predicted by a physically-based mechanistic model. This explicitly accounts for four pools of organic polymers, seven pools of organic monomers, five microbial functional groups, and inorganic N and C species. 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H. M.</au><au>Maggi, F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Similarities and differences in the sensitivity of soil organic matter (SOM) dynamics to biogeochemical parameters for different vegetation inputs and climates</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2020-12-01</date><risdate>2020</risdate><volume>34</volume><issue>12</issue><spage>2229</spage><epage>2244</epage><pages>2229-2244</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><abstract>The biogeochemical complexity of environmental models is increasing continuously and model reliability must be reanalysed when new implementations are brought about. This work aims to identify influential biogeochemical parameters that control the Soil Organic Matter (SOM) dynamics and greenhouse gas emissions in different ecosystems and climates predicted by a physically-based mechanistic model. This explicitly accounts for four pools of organic polymers, seven pools of organic monomers, five microbial functional groups, and inorganic N and C species. We first benchmarked our model against vertical SOM profiles measured in a temperate forest in North-Eastern Bavaria, Germany (Staudt and Foken in Documentation of reference data for the experimental areas of the Bayreuth Centre for Ecology and Environmental Research (BayCEER) at the Waldstein site. Univ, Bayreuth, Department of Micrometeorology, 2007). Next, we conducted a sensitivity analysis to biogeochemical parameters using modified Morris indices for target SOM pools and gas emissions from a tropical, a temperate, and a semi-arid grassland in Australia. We found that greenhouse gas emissions, the SOM stock, and the fungi-to-bacteria ratio in the top soil were more sensitive to the mortality of aerobic bacteria than other biogeochemical parameters. 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subjects Aerobic bacteria
Aquatic Pollution
Aridity
Atmospheric models
Bacteria
Biogeochemistry
Carbon dioxide
Carbon dioxide emissions
Chemistry and Earth Sciences
Climate prediction
Computational Intelligence
Computer Science
Earth and Environmental Science
Earth Sciences
Emissions
Environment
Environment models
Environmental modeling
Environmental research
Functional groups
Fungi
Grasslands
Greenhouse effect
Greenhouse gases
Math. Appl. in Environmental Science
Micrometeorology
Microorganisms
Monomers
Organic matter
Organic soils
Original Paper
Parameter identification
Parameter modification
Parameter sensitivity
Physics
Polymers
Pools
Probability Theory and Stochastic Processes
Sensitivity analysis
Soil dynamics
Soil organic matter
Soils
Statistics for Engineering
Temperate forests
Vegetation
Waste Water Technology
Water Management
Water Pollution Control
title Similarities and differences in the sensitivity of soil organic matter (SOM) dynamics to biogeochemical parameters for different vegetation inputs and climates
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